Triple
T13351970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Durotan |
E318090
|
entity |
| Predicate | opposes |
P437
|
FINISHED |
| Object | Gul'dan |
E318093
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Gul'dan | Statement: [Durotan, opposes, Gul'dan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gul'dan Context triple: [Durotan, opposes, Gul'dan]
-
A.
Gul'dan
chosen
Gul'dan is a powerful orc warlock and one of the primary antagonists in the Warcraft universe, known for his ruthless pursuit of demonic power and betrayal of his own people.
-
B.
Gulnare
Gulnare is a central female character in Lord Byron’s narrative poem "The Corsair," known for her courage, passion, and pivotal role in the story’s dramatic events.
-
C.
Gurandukht
Gurandukht was a medieval Georgian noblewoman and queen consort, known primarily as the wife of King David IV "the Builder" of Georgia.
-
D.
Gurandukht
Gurandukht was a medieval Cuman princess known from Georgian and regional Caucasian historical sources, often mentioned in the context of dynastic and political alliances.
-
E.
Güls
Güls is a district of the German city of Koblenz, situated along the Moselle River and known for its winegrowing and scenic riverside setting.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99e8c2f1c819094f0970f35f18afa |
completed | April 11, 2026, 1:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f71f49e5548190b14d09daea628e6b |
completed | May 3, 2026, 10:11 a.m. |
Created at: April 9, 2026, 9:32 p.m.